The neural network method of parameter recognition for the horizontal well testing

Author

Jiang, Meng ; Ze, Hu

Author_Institution

Sch. of Oil & Gas Eng., Chongqing Univ. of Sci. & Technol., Chongqing, China

Volume

2

fYear

2011

Firstpage

689

Lastpage

692

Abstract

The horizontal well is a very complex issue, only two situations considered, which are homogeneous and dual media infinite formation in the paper. According to self-organization, self-learning and adaptive characteristics of neural network, mathematical models built, then BP neural network classifier model constructed in order to recognize horizontal well testing parameters, at last, one example on-site given, has proved that the neural network method of parameter recognition for the horizontal well testing is very significant.

Keywords

backpropagation; geotechnical engineering; mechanical engineering computing; mechanical testing; neural nets; unsupervised learning; BP neural network classifier model; adaptive characteristics; horizontal well testing parameter; mathematical model; parameter recognition; self-learning characteristics; self-organization characteristics; Artificial neural networks; Mathematical model; Media; Reservoirs; System identification; Testing; Training; horizontal well testing; neural network; parameter recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Business Management and Electronic Information (BMEI), 2011 International Conference on

Print_ISBN

978-1-61284-108-3

Type

conf

DOI

10.1109/ICBMEI.2011.5918006

Filename

5918006